The broad goals of this project are to explore adaptation and learning in response to repeated presentation of temporal sequences of visual stimuli. These studies are motivated by broader ideas about how local circuits in the neocortex may be carrying out predictive computations on their inputs. Such ideas could lead to new insights into the function of the human cerebral cortex, and hence have many possible medical and technological applications. In the proposal, we describe preliminary data taken in collaboration with the Tank lab at Princeton. We first performed behavioral experiments in which we trained mice to lick in response to a violation of a repeated temporal sequence. This behavior was robust and emerged rapidly, often on the first day of training. Next, we used two-photon imaging to record from neurons in layer 2/3 of mouse V1. We found that neurons rapidly modified their responses during repeated presentation of temporal sequences. Most of the neurons adapted rapidly to the presentation of repeated temporal sequences of oriented spatial images, reaching essentially zero baseline response in several seconds (what we call the `transient response'). Then, these same neurons generate a strong response to a novel spatial image that violates the ongoing temporal sequence. In addition, we find a small subset of neurons (roughly 2 in 100) that produce a sustained response to repeated temporal sequences. This sustained response ramped up over several cycles of the sequence. Then, on a longer time scale, it exhibited some features of learning, such as an anticipatory shift to earlier times s well as a form of pattern completion when presented with a novel image. We propose to extend our studies in two ways: 1) consolidate our behavioral measurements over a larger cohort of animals with identical shaping and training histories; 2) study how these responses change during training in animals engaged in the behavioral task.